Pickl AI

JULY 10, 2023

It provides functions for descriptive statistics, hypothesis testing, regression analysis, time series analysis, survival analysis, and more. These packages extend the functionality of R by providing additional functions, algorithms, datasets, and visualizations.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JUNE 19, 2024

Here are some of the most common backgrounds that prepare you well: Mathematics and Statistics These disciplines provide a rock-solid understanding of data analysis, probability theory, statistical modelling, and hypothesis testing – all essential tools for extracting meaning from data.

Data Science 52

Data Science Data Scientist Hypothesis Testing Natural Language Processing 52

Pickl AI

JULY 25, 2023

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

AUGUST 21, 2023

Key Takeaways: Data Science is a multidisciplinary field bridging statistics, mathematics, and computer science to extract insights from data. The roadmap to becoming a Data Scientist involves mastering programming, statistics, machine learning, data visualization, and domain knowledge.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

JULY 23, 2023

Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases. Characterized by the three Vs: volume, velocity, and variety, big data poses unique challenges and opportunities. Data Analysis Data analysis is the heart of deriving insights from the gathered information.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Pickl AI

SEPTEMBER 4, 2023

Clean and preprocess data to ensure its quality and reliability. Statistical Analysis: Apply statistical techniques to analyse data, including descriptive statistics, hypothesis testing, regression analysis, and machine learning algorithms.

Data Analysis 52

Data Analysis Data Analysis Hypothesis Testing Machine Learning 52

Pickl AI

MAY 30, 2024

You will collect and clean data from multiple sources, ensuring it is suitable for analysis. You will perform Exploratory Data Analysis to uncover patterns and insights hidden within the data. Visualising data makes it easier to identify anomalies and understand distributions.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

AUGUST 9, 2024

Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Students should gain a foundational understanding of statistics as it applies to data analytics.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 28, 2023

Data Cleaning is a crucial step in any data analysis process, and it’s important to showcase your ability to handle messy data effectively. Data Visualization: Create compelling and informative Data Visualizations. Visual Appeal: Use clean and visually appealing Data Visualizations.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Data Visualization 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Mlearning.ai

MAY 23, 2023

Read the full blog here —  [link] Data Science Interview Questions for Freshers 1. What is Data Science? Once the exploratory steps are completed, the cleansed data is subjected to various algorithms like predictive analysis, regression, text mining, recognition patterns, etc depending on the requirements.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

NOVEMBER 6, 2023

Steps to Perform Data Visualization: Data visualization is the presentation of information and statistics using visual tools that include charts, graphs, and maps. Its goal is to create patterns in data, trends, and anomalies comprehensible to both data professionals and people without technical knowledge.

Data Visualization 52

Data Visualization Data Science Data Scientist Data Analysis 52